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Record W4294308823 · doi:10.1152/ajpheart.00044.2022

Age and sex hormones modulate left ventricle regional response to angiotensin II in male and female mice

2022· article· en· W4294308823 on OpenAlexafffund
Élisabeth Walsh‐Wilkinson, Mohamed Lamine Aidara, Audrey Morin-Grandmont, Sara-Ève Thibodeau, Juliette Gagnon, Mathieu Genest, Marie Arsenault, Jacques Couët

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersInstitute of Gender and HealthCanadian Institutes of Health ResearchGovernment of CanadaFondation Institut Universitaire de Cardiologie et de Pneumologie de Québec
KeywordsInternal medicineVentricleEndocrinologyEndocardiumMuscle hypertrophyAngiotensin IIMedicineEjection fractionStrain (injury)Left ventricular hypertrophyHeart failureBlood pressure

Abstract

fetched live from OpenAlex

We propose a new method for the study of regional strain data by analyzing individually the software-generated 48 regions of interest (ROI) from an LV wall tracing in B-mode. This helps obtain a more comprehensive profile of strain data. Using these new tools, we studied in mice how sex, sex hormones, age, or a pathological stress influenced strain parameters. We show that for similar cardiac hypertrophy, regional strain shows important differences related to sex, sex hormones, and age.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.242
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2022
Admission routes2
Has abstractyes

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